decode_url

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't cover important aspects like error handling (e.g., for malformed input), performance characteristics, or what the output looks like (e.g., decoded string format). This leaves gaps for an AI agent to understand tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple utility tool, making it easy for an AI agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (a straightforward decoding operation) and the schema's full parameter coverage, the description is minimally adequate. However, with no output schema and no annotations, it lacks details on return values or behavioral traits, leaving room for improvement in completeness for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for both parameters ('input' and 'component'), including an enum for 'component'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 without compensating for any schema gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Decode URL-encoded string' clearly states the verb (decode) and resource (URL-encoded string), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'encode_url', which performs the inverse operation, though the distinction is implied through the verb choice.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'decode_base64' for other encoding types or 'encode_url' for the reverse operation, nor does it specify contexts where URL decoding is needed (e.g., handling web data or query parameters).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.